jcf94 commented on a change in pull request #5962: URL: https://github.com/apache/incubator-tvm/pull/5962#discussion_r449464960
########## File path: python/tvm/ansor/auto_schedule.py ########## @@ -0,0 +1,206 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +""" +User interface for Ansor auto-scheduler. + +The basic schedule search process for Ansor is designed to be: +`Program sampling` -> `Performance Tuning`. + +In `Program sampling`, we use some predefined or heuristic rules to generate several initial +schedules. Based on these initial start points, we have `Performance Tuning` to apply cost model +and evolutionary search to seek for schedules with the best performance. Candidate schedules will +be measured in the target hardware. +""" + +import tvm._ffi +from tvm.runtime import Object +from .compute_dag import ComputeDAG +from .measure import LocalBuilder, LocalRunner +from . import _ffi_api + + +@tvm._ffi.register_object("ansor.HardwareParams") +class HardwareParams(Object): + """ The parameters of target hardware, this is used to guide the search process of + SearchPolicy. + + TODO(...): This is considering to merge with the new Target: + https://discuss.tvm.ai/t/rfc-tvm-target-specification/6844 + + Parameters + ---------- + num_cores : int + The number of device cores. + vector_unit_bytes : int + The width of vector units in bytes. + cache_line_bytes : int + The size of cache line in bytes. + max_unroll_vec : int + The max length of an axis to be unrolled or vectorized. + max_innermost_split_factor : int + The max split factor for the innermost tile. + """ + def __init__(self, num_cores, vector_unit_bytes, cache_line_bytes, + max_unroll_vec, max_innermost_split_factor): + self.__init_handle_by_constructor__(_ffi_api.HardwareParams, num_cores, + vector_unit_bytes, cache_line_bytes, + max_unroll_vec, max_innermost_split_factor) + + +@tvm._ffi.register_object("ansor.SearchTask") +class SearchTask(Object): + """ The meta-information of a search task. + + Parameters + ---------- + dag : ComputeDAG + The ComputeDAG for target compute declaration. + workload_key : str + The workload key for target compute declaration. + target : tvm.target.Target + The target device of this search task. + target_host : Optional[tvm.target.Target] + The target host device of this search task. + hardware_params : Optional[HardwareParams] + Hardware parameters used in this search task. + """ + def __init__(self, dag, workload_key, target, target_host=None, + hardware_params=None): + self.__init_handle_by_constructor__(_ffi_api.SearchTask, dag, + workload_key, target, target_host, + hardware_params) + + +@tvm._ffi.register_object("ansor.SearchPolicy") +class SearchPolicy(Object): + """ The base class for search policy """ + + +@tvm._ffi.register_object("ansor.EmptyPolicy") +class EmptyPolicy(SearchPolicy): + """ This is an example empty search policy which will always generate + the init state of target ComputeDAG. + """ + def __init__(self): + self.__init_handle_by_constructor__(_ffi_api.EmptyPolicy) + + +@tvm._ffi.register_object("ansor.TuneOption") +class TuneOption(Object): Review comment: Update the class name to `TuningOptions`. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
